Radiolabelled cytokines for imaging chronic inflammation

Diagnosis and particularly follow-up of chronic inflammatory disorders could be often difficult in clinical practice. Indeed, traditional radiological techniques reveal only structural tissue alterations and are not able to monitor functional changes occurring in tissues affected by chronic inflammation. The continuous advances in the knowledge of the pathophysioloy of chronic disorders, combined with the progress of radiochemistry, led to the development of new specific radiolabelled agents for the imaging of chronic diseases. In this scenario, cytokines, due to their pivotal role in such diseases, represent good candidates as radiopharmaceuticals

CT radiomics-based machine learning classification of atypical cartilaginous tumours and appendicular chondrosarcomas

Background Clinical management ranges from surveillance or curettage to wide resection for atypical to higher-grade cartilaginous tumours, respectively. Our aim was to investigate the performance of computed tomography (CT) radiomics-based machine learning for classification of atypical cartilaginous tumours and higher-grade chondrosarcomas of long bones. Methods One-hundred-twenty patients with histology-proven lesions were retrospectively included. The training cohort consisted of 84 CT scans from centre 1 (n=55 G1 or atypical cartilaginous tumours; n=29 G2-G4 chondrosarcomas). The external test cohort consisted of the CT component of 36 positron emission tomography-CT scans from centre 2 (n=16 G1 or atypical cartilaginous tumours; n=20 G2-G4 chondrosarcomas). Bidimensional segmentation was performed on preoperative CT. Radiomic features were extracted. After dimensionality reduction and class balancing in centre 1, the performance of a machine-learning classifier (LogitBoost) was assessed on the training cohort using 10-fold cross-validation and on the external test cohort. In centre 2, its performance was compared with preoperative biopsy and an experienced radiologist using McNemar's test. Findings The classifier had 81% (AUC=0.89) and 75% (AUC=0.78) accuracy in identifying the lesions in the training and external test cohorts, respectively. Specifically, its accuracy in classifying atypical cartilaginous tumours and higher-grade chondrosarcomas was 84% and 78% in the training cohort, and 81% and 70% in the external test cohort, respectively. Preoperative biopsy had 64% (AUC=0.66) accuracy (p=0.29). The radiologist had 81% accuracy (p=0.75). Interpretation Machine learning showed good accuracy in classifying atypical and higher-grade cartilaginous tumours of long bones based on preoperative CT radiomic features

3D vs. 2D MRI radiomics in skeletal Ewing sarcoma: Feature reproducibility and preliminary machine learning analysis on neoadjuvant chemotherapy response prediction

ObjectiveThe extent of response to neoadjuvant chemotherapy predicts survival in Ewing sarcoma. This study focuses on MRI radiomics of skeletal Ewing sarcoma and aims to investigate feature reproducibility and machine learning prediction of response to neoadjuvant chemotherapy. Materials and methodsThis retrospective study included thirty patients with biopsy-proven skeletal Ewing sarcoma, who were treated with neoadjuvant chemotherapy before surgery at two tertiary sarcoma centres. 7 patients were poor responders and 23 were good responders based on pathological assessment of the surgical specimen. On pre-treatment T1-weighted and T2-weighted MRI, 2D and 3D tumour segmentations were manually performed. Features were extracted from original and wavelet-transformed images. Feature reproducibility was assessed through small geometrical transformations of the regions of interest mimicking multiple manual delineations, and intraclass correlation coefficient >0.75 defined feature reproducibility. Feature selection also consisted of collinearity and significance analysis. After class balancing in the training cohort, three machine learning classifiers were trained and tested on unseen data using hold-out cross-validation. Results1303 (77%) 3D and 620 (65%) 2D radiomic features were reproducible. 4 3D and 4 2D features passed feature selection. Logistic regression built upon 3D features achieved the best performance with 85% accuracy (AUC=0.9) in predicting response to neoadjuvant chemotherapy. ConclusionCompared to 2D approach, 3D MRI radiomics of Ewing sarcoma had superior reproducibility and higher accuracy in predicting response to neoadjuvant chemotherapy, particularly when using logistic regression classifier

Disease-Modifying Therapies and Coronavirus Disease 2019 Severity in Multiple Sclerosis

Objective: This study was undertaken to assess the impact of immunosuppressive and immunomodulatory therapies on the severity of coronavirus disease 2019 (COVID-19) in people with multiple sclerosis (PwMS). Methods: We retrospectively collected data of PwMS with suspected or confirmed COVID-19. All the patients had complete follow-up to death or recovery. Severe COVID-19 was defined by a 3-level variable: mild disease not requiring hospitalization versus pneumonia or hospitalization versus intensive care unit (ICU) admission or death. We evaluated baseline characteristics and MS therapies associated with severe COVID-19 by multivariate and propensity score (PS)-weighted ordinal logistic models. Sensitivity analyses were run to confirm the results. Results: Of 844 PwMS with suspected (n = 565) or confirmed (n = 279) COVID-19, 13 (1.54%) died; 11 of them were in a progressive MS phase, and 8 were without any therapy. Thirty-eight (4.5%) were admitted to an ICU; 99 (11.7%) had radiologically documented pneumonia; 96 (11.4%) were hospitalized. After adjusting for region, age, sex, progressive MS course, Expanded Disability Status Scale, disease duration, body mass index, comorbidities, and recent methylprednisolone use, therapy with an anti-CD20 agent (ocrelizumab or rituximab) was significantly associated (odds ratio [OR] = 2.37, 95% confidence interval [CI] = 1.18-4.74, p = 0.015) with increased risk of severe COVID-19. Recent use (<1 month) of methylprednisolone was also associated with a worse outcome (OR = 5.24, 95% CI = 2.20-12.53, p = 0.001). Results were confirmed by the PS-weighted analysis and by all the sensitivity analyses. Interpretation: This study showed an acceptable level of safety of therapies with a broad array of mechanisms of action. However, some specific elements of risk emerged. These will need to be considered while the COVID-19 pandemic persists

COVID-19 Severity in Multiple Sclerosis: Putting Data Into Context

Background and objectives: It is unclear how multiple sclerosis (MS) affects the severity of COVID-19. The aim of this study is to compare COVID-19-related outcomes collected in an Italian cohort of patients with MS with the outcomes expected in the age- and sex-matched Italian population. Methods: Hospitalization, intensive care unit (ICU) admission, and death after COVID-19 diagnosis of 1,362 patients with MS were compared with the age- and sex-matched Italian population in a retrospective observational case-cohort study with population-based control. The observed vs the expected events were compared in the whole MS cohort and in different subgroups (higher risk: Expanded Disability Status Scale [EDSS] score > 3 or at least 1 comorbidity, lower risk: EDSS score ≤ 3 and no comorbidities) by the χ2 test, and the risk excess was quantified by risk ratios (RRs). Results: The risk of severe events was about twice the risk in the age- and sex-matched Italian population: RR = 2.12 for hospitalization (p < 0.001), RR = 2.19 for ICU admission (p < 0.001), and RR = 2.43 for death (p < 0.001). The excess of risk was confined to the higher-risk group (n = 553). In lower-risk patients (n = 809), the rate of events was close to that of the Italian age- and sex-matched population (RR = 1.12 for hospitalization, RR = 1.52 for ICU admission, and RR = 1.19 for death). In the lower-risk group, an increased hospitalization risk was detected in patients on anti-CD20 (RR = 3.03, p = 0.005), whereas a decrease was detected in patients on interferon (0 observed vs 4 expected events, p = 0.04). Discussion: Overall, the MS cohort had a risk of severe events that is twice the risk than the age- and sex-matched Italian population. This excess of risk is mainly explained by the EDSS score and comorbidities, whereas a residual increase of hospitalization risk was observed in patients on anti-CD20 therapies and a decrease in people on interferon

DMTs and Covid-19 severity in MS: a pooled analysis from Italy and France

We evaluated the effect of DMTs on Covid-19 severity in patients with MS, with a pooled-analysis of two large cohorts from Italy and France. The association of baseline characteristics and DMTs with Covid-19 severity was assessed by multivariate ordinal-logistic models and pooled by a fixed-effect meta-analysis. 1066 patients with MS from Italy and 721 from France were included. In the multivariate model, anti-CD20 therapies were significantly associated (OR = 2.05, 95%CI = 1.39–3.02, p < 0.001) with Covid-19 severity, whereas interferon indicated a decreased risk (OR = 0.42, 95%CI = 0.18–0.99, p = 0.047). This pooled-analysis confirms an increased risk of severe Covid-19 in patients on anti-CD20 therapies and supports the protective role of interferon

Scientific production and impact of nuclear medicine in Europe: How do we publish?

We performed a bibliometric search covering a 1-year period to evaluate the number and the scientific "weight" of nuclear medicine papers published from European as compared with other countries. The scientific impact of our discipline was evaluated according to the impact factor of each publication, and we also aimed to identify those countries and topics that are making the principal contributions to the development of our discipline. To this end, a search on MEDLINE (PubMed) was run to find all peer-reviewed articles published between April 2002 and May 2003, using isotope definitions as search terms. A total of 3,292 publications were identified. Of these, 650 were of no nuclear medicine interest, 229 were reviews and 82 had no country specified. In absolute numbers, Europe leads research in nuclear medicine (939 papers, 38.9%) followed by the USA (608 papers, 25.2%). Among European countries, Germany is the nation that is currently making the greatest contribution to the scientific production of nuclear medicine in Europe. Articles concerning the use of nuclear medicine in oncology account for more than one-quarter of all published nuclear medicine papers

Imaging active lymphocytic infiltration in coeliac disease with iodine-123-interleukin-2 and the response to diet

Coeliac disease is diagnosed by the presence of specific antibodies and a jejunal biopsy showing mucosal atrophy and mononuclear cell infiltration. Mucosal cell-mediated immune response is considered the central event in the pathogenesis of coeliac disease, and untreated coeliac patients show specific features of T-cell activation in the small intestine. Here we describe the use of iodine-123-interleukin-2 scintigraphy in coeliac patients as a non-invasive tool for detection of lymphocytic infiltration in the small bowel and its use for therapy follow-up, and we demonstrate the specificity of binding of labelled-IL2 to activated lymphocytes by ex-vivo autoradiography of jejunal biopsies. I-123-IL2 was administered i.v, [74 MBq (2 mCi)], and gamma camera images were acquired after I h. Ten patients were studied with I-123-IL2 scintigraphy at diagnosis and seven were also investigated after 12-19 months of gluten-free diet. Results were expressed as target-to-background radioactivity ratios in six different bowel regions before and after the diet. At the time of diagnosis all patients showed a signifi- cantly higher bowel uptake of I-123-IL2 than normal subjects (P<0.003 in all regions). A significant correlation was found between jejunal radioactivity and the number of IL2R+ve lymphocytes per millimetre of jejunal mucosa as detected by immunostaining of jejunal biopsy (r(2)=0.66; P=0.008), Autoradiography of jejunal biopsies confirmed that labelled-IL2 only binds to activated T-lymphocytes infiltrating the gut mucosa. After 1 year of the diet, bowel uptake of I-123-IL2 significantly decreased in five out of six regions (P<0.03), although two patients still had a positive IL2 scintigraphy in one region. We conclude that I-123-IL2 scintigraphy is a sensitive non-invasive technique for assessing in vivo the presence of activated mononuclear cells in the bowel of patients affected by coeliac disease. Unlike jejunal biopsy, this method provides information from the whale intestine and gives a non-invasive measure of the effectiveness of the gluten-free diet